Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add magnus919/agent-skills --skill product-experimentationgit clone --depth 1 https://github.com/magnus919/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/magnus919/agent-skills/product-experimentation)<a href="https://agentmods.dev/skills/magnus919/agent-skills/product-experimentation"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/product-experimentation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/magnus919/agent-skills/product-experimentation"><img src="https://agentmods.dev/badge/skills/magnus919/agent-skills/product-experimentation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00107 | $0.02094 |
| Opus 5 | $0.00053 | $0.01047 |
| Sonnet 5 | $0.00021 | $0.00419 |
| Haiku 4.5 | $0.00011 | $0.00209 |
Grade A, and why
product-experimentation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Experimentation
End-to-end product experimentation: from assumption mapping through method selection, instrumentation, guardrail enforcement, and decision-readout that updates the product roadmap. Owns the complete experiment workflow; routes statistical design and rollout mechanics to specialist skills.
Pipeline
ASSUMPTIONS → [HYPOTHESIS] → [METHOD SELECT] → [INSTRUMENT] → [RUN] → [DECIDE] → [RECORD]
| | | | | |
Experiment Qualitative Tracking Guardrail Decision Readout
brief Prototype plan monitor rules learning
Operational
Quantitative
Loading Guide
Load only the reference or template relevant to the task. Do not load every file at once.
| File | Load when |
|---|---|
| references/discovery-brief.md | You need to understand how experimentation concepts map across skills and where this skill's boundaries are |
| references/method-selection.md | Choosing among qualitative, prototype, operational, and quantitative test methods |
| references/guardrails-and-ethics.md | Defining guardrail metrics, ethical boundaries, stopping rules, and decision ownership |
| references/experiment-readout.md | Producing a decision-impact readout that updates the roadmap or decision record |
| templates/experiment-brief.md | Filling out a structured experiment brief from an assumption |
| templates/assumption-map.md | Mapping assumptions to risk, evidence, and testability before designing experiments |
| templates/guardrail-and-decision-rule.md | Recording guardrails, stopping rules, and decision criteria for an experiment |
| templates/readout-learning-entry.md | Documenting experiment outcome and updating the roadmap, decision log, or lifecycle evidence |
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 8.2 KB
- README.md 4.2 KB
- references/discovery-brief.md 5.9 KB
- references/experiment-readout.md 2.6 KB
- references/guardrails-and-ethics.md 5.4 KB
- references/method-selection.md 4.6 KB
- templates/assumption-map.md 1.8 KB
- templates/experiment-brief.md 2.1 KB
- templates/guardrail-and-decision-rule.md 2.4 KB
- templates/readout-learning-entry.md 1.6 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 135 lines · 107 tokens per session scan A 66d7757be904
product-experimentation is a skill published in the GitHub repository magnus919/agent-skills (76 stars, last pushed yesterday), licensed MIT. It adds 107 tokens to every session and 2,094 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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